API-Football MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add API-Football as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to API-Football. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in API-Football?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About API-Football MCP Server
Empower your AI agent to orchestrate your football tracking and fan engagement with API-Football, the premier API for global football data. By connecting API-Football to your agent, you transform complex fixture auditing, live score monitoring, and player statistical analysis into a natural conversation. Your agent can instantly retrieve real-time results for over 1,000 leagues, access detailed standings, and even perform head-to-head comparisons between teams without you ever needing to navigate multiple sports apps or websites. Whether you are conducting a seasonal performance audit or coordinating real-time match alerts, your agent acts as a real-time sports data coordinator, providing accurate results from a single, authorized source.
LlamaIndex agents combine API-Football tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Live Orchestration — Retrieve real-time scores and match status for thousands of games across the globe.
- Standings Auditing — Access comprehensive league tables and team rankings for major global competitions.
- Fixture Management — Retrieve scheduled matches and fixture lists for specific dates and leagues.
- Deep Metadata — Access detailed profile data for teams and players, including performance stats.
- H2H Comparison — Perform historical head-to-head audits between any two teams to gauge competitive history.
The API-Football MCP Server exposes 8 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect API-Football to LlamaIndex via MCP
Follow these steps to integrate the API-Football MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 8 tools from API-Football
Why Use LlamaIndex with the API-Football MCP Server
LlamaIndex provides unique advantages when paired with API-Football through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine API-Football tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain API-Football tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query API-Football, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what API-Football tools were called, what data was returned, and how it influenced the final answer
API-Football + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the API-Football MCP Server delivers measurable value.
Hybrid search: combine API-Football real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query API-Football to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying API-Football for fresh data
Analytical workflows: chain API-Football queries with LlamaIndex's data connectors to build multi-source analytical reports
API-Football MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect API-Football to LlamaIndex via MCP:
get_fixtures
List match fixtures
get_league_topscorers
Get top scorers
get_player_info
Get player statistics
get_standings
Get league standings
get_team_info
Get team details
list_leagues
List football leagues
list_live_fixtures
Get live matches
search_football_teams
Search for teams
Example Prompts for API-Football in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with API-Football immediately.
"Show me all live football matches in the Premier League (ID: 39)."
"Get the latest standings for the Brasileirão Serie A (ID: 71) season 2023."
"What is the H2H history between Flamengo (ID: 127) and Fluminense (ID: 124)?"
Troubleshooting API-Football MCP Server with LlamaIndex
Common issues when connecting API-Football to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAPI-Football + LlamaIndex FAQ
Common questions about integrating API-Football MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect API-Football with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect API-Football to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.